Curriculum

Basic Track

• AI Foundations & Project Cycle: Understand how AI is built, used, and evaluated, end to end
• Data Literacy: Read, question, and visualise data confidently
• Math for AI: Grasp the statistics and probability ideas behind AI
• Generative AI: Understand how tools like ChatGPT actually work, and their limits
• Python Programming: Write real, working code from day one
• Responsible AI: Understand bias, fairness, and ethical implications of building and using AI systems

Advance Track: Projects

• Build an AI Model: Train and use your own image/gesture recognition model
• SDG-Linked Data Project: Design a real AI-enabled solution to a community problem
• Applied AI Literacy: Bridge the gap between AI theory and real-world tools
• Portfolio Building: Start creating a track record of practical AI implementations

Basic Track

• Evaluating AI Models: Learn how to judge whether an AI model is actually working well
• Computer Vision: Teach computers to understand images
• Natural Language Processing: Teach computers to understand language
• Advanced Python: Write more powerful, complex programs
• Responsible AI: Explore real-world AI bias cases and learn to evaluate models for fairness and safety

Advance Track: Projects

• Computer Vision Mini-App: Build a working image-recognition application
• NLP / Chatbot App: Build a working text-understanding application
• Advanced Prompt Engineering: Create complex system prompts for targeted outputs
• Project Deployment: Learn how to showcase your working AI applications

Basic Track

• Computer Systems: Understand how computers actually work, inside and out
• Python Programming (Core): Build serious programming skills used throughout the rest of the course
• Data Handling with Pandas: Analyse and visualise real-world data like a professional
• Digital Ethics & Law: Understand the rules and responsibilities of the digital world
• Applied AI: Go beyond chat tools and use AI capabilities through code
• Responsible AI: Analyse AI ethics frameworks, data privacy laws, and build AI responsibly

Advance Track: Projects

• Data-Driven Mini Tool: Build a tool that analyses and visualises real data
• Applied AI Mini Tool: Build a working app powered by a real AI capability
• Interactive Dashboards: Build visual interfaces for your data analysis
• Custom Python Scripts: Automate complex tasks with Python code
• Large Language Models (LLMs): Understand how LLMs work, fine-tuning basics, and build prompt-engineered applications

Basic Track

• Functions, Files & Data Structures: Write organised, professional-grade Python programs
• Computer Networks: Understand how the internet and connected systems work
• Databases & SQL: Design, store, and query real data like an industry professional
• Applied AI & GenAI: Combine data skills with AI to build complete, real workflows
• Responsible AI: Apply ethical AI principles to your capstone projects and real-world deployments

Advance Track: Projects

• ML-Backed Application: Build an app powered by a real trained AI model and a database
• GenAI-Integrated Tool: Build a tool that combines Generative AI with your own data
• Data Analysis Dashboard: Build a complete, portfolio-ready data analytics project
• Industry-level Architecture: Connect databases, Python, and APIs into one system
• Large Language Models (LLMs): Integrate LLMs into full-stack applications with custom data retrieval and system prompting